A Machine Learning Approach to Volume Tracking in Multiphase Flow Simulations

datacite.relatedItem.firstPage39
datacite.relatedItem.issue2
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2311-5521
datacite.relatedItem.relationTypeIsPublishedIn
datacite.relatedItem.titleFluids
datacite.relatedItem.volume10
dc.contributor.authorAaron Mak
dc.contributor.authorMehdi Raessi
dc.date.accessioned2025-04-16T12:58:49Z
dc.date.available2025-04-16T12:58:49Z
dc.date.issued2025
dc.identifier.doihttps://doi.org/10.3390/fluids10020039
dc.identifier.otherjz000143-0044
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/18950
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc530
dc.titleA Machine Learning Approach to Volume Tracking in Multiphase Flow Simulations
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/18951
dcat.distribution.supplierxmlhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/18952
dspace.entity.typeDataset
relation.isDistributionOfDataset8aad6c58-06b8-4f48-af11-9ab8db51ae4e
relation.isDistributionOfDataset8b273fd9-ebbb-400f-9be3-8b46f163c189
relation.isDistributionOfDataset51b0c192-5d62-42dd-b249-ff73e64f4383
relation.isDistributionOfDataset.latestForDiscovery8aad6c58-06b8-4f48-af11-9ab8db51ae4e
wdm.archivematicaaipuuid.original326d8a08-248c-4aa4-99a8-95c84333bf85

Files

Collections